|
|
Absolute deviation, 绝对离差
+ ~2 S; i, [' |) V) ]Absolute number, 绝对数
! y3 c/ b0 T0 r$ p" FAbsolute residuals, 绝对残差
" e$ E8 e5 T8 @# _+ z) mAcceleration array, 加速度立体阵
/ X' J5 \1 f0 ~ w5 q9 V3 f, xAcceleration in an arbitrary direction, 任意方向上的加速度
- J8 K# E: N' H5 O4 pAcceleration normal, 法向加速度
6 j' q. D b* P, K; B+ G8 pAcceleration space dimension, 加速度空间的维数
4 N5 d4 l2 I* W" ?3 v5 IAcceleration tangential, 切向加速度
1 O s3 z6 S2 @! x! _, `+ NAcceleration vector, 加速度向量
# r, B( O- |- iAcceptable hypothesis, 可接受假设9 K0 \8 x* ~, Z
Accumulation, 累积& K! M" s# c/ X" e b# @9 U" ^
Accuracy, 准确度/ Z0 k- m% c2 a$ O6 J
Actual frequency, 实际频数
" y w: e/ G0 l7 z% OAdaptive estimator, 自适应估计量 ^" P* f9 T- g4 R2 B* {
Addition, 相加
# A/ @+ [+ V, _) L `4 S! F5 JAddition theorem, 加法定理
+ p5 t; E( x* y: QAdditivity, 可加性
. g7 q: x" P7 {: EAdjusted rate, 调整率
, ]# y+ v* o2 Q* P9 q3 x; IAdjusted value, 校正值6 d, e! _9 [( f7 O4 L" `+ n
Admissible error, 容许误差% B6 B9 H+ F" i9 j6 ?$ |& Y8 x
Aggregation, 聚集性 G! \5 `- @1 z' Q1 y0 a
Alternative hypothesis, 备择假设4 A$ M6 Y1 S! X2 B1 L
Among groups, 组间
7 H. J- z4 r7 ^2 L; Q. xAmounts, 总量
' O6 g, M7 l( g, H. N9 ]1 CAnalysis of correlation, 相关分析6 U2 e2 b# k4 C, ]( f j
Analysis of covariance, 协方差分析
0 ?# {/ ^0 G+ _# n- x0 H4 h6 RAnalysis of regression, 回归分析
; D4 C" p1 V; K' ^5 p# KAnalysis of time series, 时间序列分析
. v. J4 g# o3 m' B8 X0 FAnalysis of variance, 方差分析& E( s9 P/ x% p3 [4 G% I
Angular transformation, 角转换
. J# K, J8 W1 t- ^6 u( K& B2 s) cANOVA （analysis of variance）, 方差分析
! Q, A- {$ {! j3 `' B$ r% f2 ?6 j, {ANOVA Models, 方差分析模型( W& b# Q' _/ ?& T. s
Arcing, 弧/弧旋
5 a3 D3 E2 ]- q0 z6 U9 lArcsine transformation, 反正弦变换6 @; H6 D$ ^. z: u
Area under the curve, 曲线面积' n6 \% I E$ z4 ]% D# g* p
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
! K0 i5 V" D0 Z- U3 ? e; x$ GARIMA, 季节和非季节性单变量模型的极大似然估计
?2 v) \2 | o7 s% _( ]% ]- |- VArithmetic grid paper, 算术格纸, o0 R8 ]& X5 k0 ~( n
Arithmetic mean, 算术平均数/ u- [; `! K4 z7 \8 c
Arrhenius relation, 艾恩尼斯关系8 m1 E% `3 S1 ?2 S1 N% V3 M
Assessing fit, 拟合的评估& Z/ U B9 Y+ h" \
Associative laws, 结合律" o, ?# a2 B$ q: C/ r- e
Asymmetric distribution, 非对称分布* l" i" A- }3 k6 }' K0 q
Asymptotic bias, 渐近偏倚
% t: k7 d" D" {2 e% o: fAsymptotic efficiency, 渐近效率
; }" W. {/ `. R! c& B- I' M' yAsymptotic variance, 渐近方差
- I" ~2 f+ y' d% p( P6 PAttributable risk, 归因危险度
/ X7 @" t8 F% Z" T! GAttribute data, 属性资料
, [4 E3 \' l- j: {" M: sAttribution, 属性$ Z+ W) A3 b1 @* e5 @
Autocorrelation, 自相关: K+ }& S) I# U, o) A
Autocorrelation of residuals, 残差的自相关 r. q- w5 U s. f) ~& j/ c9 n! ]# J
Average, 平均数
" _5 ^, k4 C3 H" i. r% o$ FAverage confidence interval length, 平均置信区间长度, e% r0 } ?, j2 t# c4 u
Average growth rate, 平均增长率5 p6 F: l8 x: N
Bar chart, 条形图
. _9 [' S8 P4 ]# b7 G# i" \Bar graph, 条形图
" S! ^4 ~0 ?* x& v) oBase period, 基期' ^* i# x6 n9 V& a" W# p
Bayes' theorem , Bayes定理; u: v/ E+ i! L5 L" y
Bell-shaped curve, 钟形曲线
! D1 K) g' R+ F) @Bernoulli distribution, 伯努力分布
( o" a0 @; z4 p' d; @3 l. H& }Best-trim estimator, 最好切尾估计量* X0 u2 O% J/ x/ e" d* l9 N
Bias, 偏性7 L: _+ i% M0 }
Binary logistic regression, 二元逻辑斯蒂回归, h% u; o( P- ^! _4 |, I
Binomial distribution, 二项分布: x6 B: J% j! w' t/ c% h6 j4 \% l9 x
Bisquare, 双平方
0 U) I/ a% G8 n1 L( y8 n0 F) |Bivariate Correlate, 二变量相关
% \% J1 O$ ?) m$ wBivariate normal distribution, 双变量正态分布
4 P3 f+ c' N/ R- a& eBivariate normal population, 双变量正态总体. V9 [1 H% s0 K0 z! u) e5 B$ [
Biweight interval, 双权区间
* Q4 h3 M# W5 i1 o, q' rBiweight M-estimator, 双权M估计量
% f% F- q% F' }. P- Z& ?$ E" XBlock, 区组/配伍组* m$ e7 N( D H
BMDP(Biomedical computer programs), BMDP统计软件包
. |7 h! h" J ^8 \4 y% H! sBoxplots, 箱线图/箱尾图8 M& _( U3 M9 @
Breakdown bound, 崩溃界/崩溃点
% D' b6 Z5 M9 \& y2 |Canonical correlation, 典型相关# p4 @. A/ C a0 p; }% ]
Caption, 纵标目
) t, K) v& }# }- DCase-control study, 病例对照研究 q' j4 i$ p. S2 N/ J: _
Categorical variable, 分类变量. S; A- `& k+ F4 m* _" x% ^# k: p
Catenary, 悬链线4 j4 t! P2 ?+ b5 C$ p( H0 B8 h
Cauchy distribution, 柯西分布
9 L5 ?/ P$ h- y- z( g4 X. O9 PCause-and-effect relationship, 因果关系
0 w) \9 [3 J4 R2 OCell, 单元1 a* E5 J7 z. B% x
Censoring, 终检
7 X% ?+ m- H9 LCenter of symmetry, 对称中心, t! W( r" y% l( w) s
Centering and scaling, 中心化和定标
8 i, o" u+ L) w; KCentral tendency, 集中趋势
5 x+ [! e, d6 R; w- U/ |Central value, 中心值
: |1 D2 |- M! WCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
6 E# P" a( q3 H7 i" Z$ G) ^- QChance, 机遇
, F0 m" J5 W# o" R) V4 X1 bChance error, 随机误差& H5 Y, {8 V' h, `+ U0 R' i
Chance variable, 随机变量
# Z2 U# M4 F& t3 d: I+ jCharacteristic equation, 特征方程) t) a' o, N) g$ [0 ?' E% D
Characteristic root, 特征根
/ \" t7 y2 K6 D! C5 qCharacteristic vector, 特征向量) s* |/ B9 [$ E, U" m3 n+ Y! Y
Chebshev criterion of fit, 拟合的切比雪夫准则3 a1 ~6 q9 z9 O# N
Chernoff faces, 切尔诺夫脸谱图
+ o+ R; `8 T0 PChi-square test, 卡方检验/χ2检验# ]- p1 S3 L- U7 A
Choleskey decomposition, 乔洛斯基分解( x0 b5 e% |% ]( e4 S( a7 o
Circle chart, 圆图
( m0 O7 u4 H# YClass interval, 组距# }9 c$ D# t' L; Z& F
Class mid-value, 组中值
. m& g- f J& Z! Z; T8 cClass upper limit, 组上限. ]# O% i, M& c o- F
Classified variable, 分类变量
) Q( P3 ~ ]% ^+ n! I1 {8 aCluster analysis, 聚类分析! W/ V/ \& y; Q* z+ U' p: P
Cluster sampling, 整群抽样
: d: B/ P" n. l5 E, |1 JCode, 代码9 ], o( U8 q! z$ M- m
Coded data, 编码数据1 D- R, s d% A$ |$ U( V. ]9 Y
Coding, 编码
9 t6 U6 c/ {4 r. z% @( ^: ZCoefficient of contingency, 列联系数
- ^) w* }3 F. f$ z9 B, Q4 q% QCoefficient of determination, 决定系数
1 U6 r1 V" R- |9 I$ FCoefficient of multiple correlation, 多重相关系数
0 e) p7 F- z7 k8 H+ h9 GCoefficient of partial correlation, 偏相关系数/ y5 v2 O6 I% {/ S5 v9 M
Coefficient of production-moment correlation, 积差相关系数+ t w; m0 J. [
Coefficient of rank correlation, 等级相关系数
, C- n9 V1 Z" R2 \0 C( XCoefficient of regression, 回归系数
% F8 Q6 Z/ b) B( u" KCoefficient of skewness, 偏度系数
8 [" s9 c* z/ SCoefficient of variation, 变异系数" o" T" |' P6 T/ W) `# [: S+ w; `
Cohort study, 队列研究1 j# @- X# y( n2 U2 c
Column, 列
* Y8 x+ k' v" l$ nColumn effect, 列效应
% A& D! e" E. e% K; l# C# zColumn factor, 列因素' Y0 k" T' i+ E8 q7 D
Combination pool, 合并/ b2 e4 {# v" B/ {
Combinative table, 组合表
1 D7 z9 Z, J) j8 c$ v VCommon factor, 共性因子
0 V6 R5 p& z, L' L& [$ @$ M2 kCommon regression coefficient, 公共回归系数/ A& y3 P, ^6 M1 U3 D' u. H3 N/ L8 A
Common value, 共同值) A0 G/ V% Q( ~# S/ f3 u
Common variance, 公共方差5 g |% q( {2 {# Y
Common variation, 公共变异/ Z- C4 b" i: g& H/ T
Communality variance, 共性方差2 C- w. n/ H: H' X8 S: s
Comparability, 可比性# u% ~6 _& X( p) W
Comparison of bathes, 批比较
( v' z! t6 D. {" VComparison value, 比较值
1 R! \2 g7 A. }# _4 FCompartment model, 分部模型4 f _; l% R# J2 ?7 O! B; k0 ]5 F
Compassion, 伸缩
! Z) z* y1 c. U' E, nComplement of an event, 补事件$ U3 u( h/ l9 v# i4 q
Complete association, 完全正相关2 a5 J$ a9 M+ h7 _6 r9 A+ E& |
Complete dissociation, 完全不相关
$ e% b; i8 U" F% R, C5 zComplete statistics, 完备统计量
# l t8 p2 W. Y' |# h: g0 U6 z2 C# eCompletely randomized design, 完全随机化设计
! o7 U4 H5 s. wComposite event, 联合事件% I. s6 Z2 R' V( k
Composite events, 复合事件/ p; T4 N8 k& W% f7 n1 B; b/ X
Concavity, 凹性
6 \9 m/ W7 t$ Q; {6 @) QConditional expectation, 条件期望
6 U& j5 ^! b, [/ t$ x( |! C" XConditional likelihood, 条件似然
8 o# U b0 H+ c5 wConditional probability, 条件概率( ~3 r5 B) G' `, {) ~
Conditionally linear, 依条件线性
4 i$ M8 L) H5 |% r1 X& E% J, Z) uConfidence interval, 置信区间: w% w3 ]( K" J+ b
Confidence limit, 置信限
( p; ^; C# g0 K& R' s; Z8 V! b tConfidence lower limit, 置信下限
1 e2 W- u8 W0 V0 V' OConfidence upper limit, 置信上限1 q; ?8 R2 ^3 G1 R ~; Y- ^2 N" O
Confirmatory Factor Analysis , 验证性因子分析/ C: C$ |! X! F$ d* n& _$ Y
Confirmatory research, 证实性实验研究2 I- {6 V6 z" S5 S7 v5 f9 n# ~
Confounding factor, 混杂因素
1 ~4 A3 Q; v: s& ]Conjoint, 联合分析: M: J8 b5 ]+ L' G
Consistency, 相合性& ~! B0 ?9 R/ e# H5 S) N0 Y" l! _
Consistency check, 一致性检验
9 `0 G7 h. p7 L* SConsistent asymptotically normal estimate, 相合渐近正态估计1 C+ \$ V/ @7 \. J( @
Consistent estimate, 相合估计: X0 ?8 A' C% h! a8 |. N* R
Constrained nonlinear regression, 受约束非线性回归9 `7 ?/ p h$ _) k/ ~' x
Constraint, 约束. u% V. d- R: X) C5 z5 h
Contaminated distribution, 污染分布* o5 R% I3 l0 ]3 s, P
Contaminated Gausssian, 污染高斯分布
' u/ {) O+ T8 g6 c! B; n) ?, xContaminated normal distribution, 污染正态分布
- v/ y3 ]* V' [6 [ u& ZContamination, 污染
+ k7 [5 g, p0 |3 E0 A- R+ @Contamination model, 污染模型' |2 \& \! b& H, H
Contingency table, 列联表9 Z6 @; b" K) `
Contour, 边界线
S2 [0 ^0 }( R5 I, MContribution rate, 贡献率
9 [2 l7 v) [! j8 {: YControl, 对照! Y6 C- y- W" Q/ F
Controlled experiments, 对照实验
% c6 t* X0 s* a! p& vConventional depth, 常规深度
) @1 M/ A/ \2 @Convolution, 卷积
4 I. D8 r/ b$ A# FCorrected factor, 校正因子0 }* z# |( t. h1 u( T' c7 j: c
Corrected mean, 校正均值7 \( {+ t. u# d# u% g" k Q' e
Correction coefficient, 校正系数( e6 D D/ [. D
Correctness, 正确性! o! T/ C3 W i
Correlation coefficient, 相关系数
$ x2 t, D0 R4 W/ G- l- t, J# _+ JCorrelation index, 相关指数
$ [& ?' V/ T o2 CCorrespondence, 对应
+ w" Z( i! g1 ^. j5 V1 WCounting, 计数
' f- s' Q# u1 M- M/ RCounts, 计数/频数
$ J3 p( g6 Z5 }9 ~! [- {Covariance, 协方差
3 U% K3 S0 G0 S! n1 x4 y N1 F6 WCovariant, 共变 ( o: z3 Z M$ d# h9 K
Cox Regression, Cox回归
6 B) P ^! v) X. n" H! T2 ECriteria for fitting, 拟合准则
3 c. V* r, c) }# ]) q& rCriteria of least squares, 最小二乘准则: E% H- h$ ?. D8 h$ Z9 J: i
Critical ratio, 临界比
J c2 x: S1 aCritical region, 拒绝域, y0 f0 w( ~0 ?9 G
Critical value, 临界值
4 u5 O4 \' x ` k E. UCross-over design, 交叉设计! D' W9 i6 V9 l
Cross-section analysis, 横断面分析# j# ]0 A$ h8 L. L6 t
Cross-section survey, 横断面调查
% u4 \5 ^7 n5 b7 F' _Crosstabs , 交叉表
+ a( m$ j6 K7 _4 W5 }3 O! \Cross-tabulation table, 复合表
0 ]2 @3 _6 b/ U$ v$ N' X2 U6 fCube root, 立方根
: R- ^- H G" D) l- z1 yCumulative distribution function, 分布函数! m2 O& L5 J" F
Cumulative probability, 累计概率( ?' {6 D I* O
Curvature, 曲率/弯曲6 x- e; B; R3 @# d& l$ P( W
Curvature, 曲率* h& e* J2 N8 f
Curve fit , 曲线拟和
9 E$ h2 P# @8 ~* E/ f3 w) Y0 kCurve fitting, 曲线拟合2 {5 Z7 o0 R$ y3 i2 c
Curvilinear regression, 曲线回归
8 F- ^( L8 R5 m, _Curvilinear relation, 曲线关系0 u/ D4 ?+ Y% ?" u2 h. Z. Z
Cut-and-try method, 尝试法
5 h2 H/ ^$ X2 g& J Y# ~# GCycle, 周期
/ e5 g6 E" p9 X0 ^; B* t3 }' ^, \Cyclist, 周期性& |& r$ K. I3 M4 n. k8 W: N
D test, D检验
9 r" v$ Z V7 aData acquisition, 资料收集
/ e4 |+ N) P# I. ?2 }Data bank, 数据库; w! Z4 p1 m* o5 H$ ]5 H
Data capacity, 数据容量6 P6 Q" d) B+ O4 ~; `4 k
Data deficiencies, 数据缺乏
. F; I6 R# j8 ~# }Data handling, 数据处理9 R: y% k- o$ B' \' \7 Z! w
Data manipulation, 数据处理
9 v. o6 i( ?! H: u. C2 T+ u) aData processing, 数据处理
) N% J' J, e+ T" n! ~+ qData reduction, 数据缩减
3 i0 D$ E* h, m: e! f7 NData set, 数据集3 y. R, }: u1 Y5 M5 p5 @" k
Data sources, 数据来源5 v6 c5 G4 [/ f( q3 [0 B7 \
Data transformation, 数据变换9 H+ I( g; \. s, }6 |
Data validity, 数据有效性' Q( p; s+ O$ h$ U N1 W" R
Data-in, 数据输入. i4 q0 y+ X8 r5 h% R u% a
Data-out, 数据输出
, N( \3 i! i' I* \6 {# Y) |Dead time, 停滞期+ d) Y+ \, i, \ V6 e8 K8 g
Degree of freedom, 自由度
" [* _5 `2 Q# {2 c5 a5 R8 b6 yDegree of precision, 精密度: ]7 X6 I$ Z2 Q( j: i% n$ v
Degree of reliability, 可靠性程度
: R- a6 f. e0 n* R+ j7 RDegression, 递减
; {& i% A8 D5 W7 S8 B' d- DDensity function, 密度函数' Q, N1 q" W5 h* n: {
Density of data points, 数据点的密度
! T7 w" w2 g; V7 eDependent variable, 应变量/依变量/因变量7 ~- a- n' ^) j4 i5 |/ f
Dependent variable, 因变量0 B% D3 g" Z3 h1 x) [
Depth, 深度4 z7 Z# O2 E1 `: c, @
Derivative matrix, 导数矩阵. A( A/ C& R# m: l% r x
Derivative-free methods, 无导数方法
; E8 c3 ^- P1 _# {Design, 设计
4 u5 ~& B& u9 O, r) aDeterminacy, 确定性
0 ^/ g# X$ P* ^) B/ dDeterminant, 行列式& E$ n2 B: ]( Z6 m* U! C3 X# q* v
Determinant, 决定因素
. j% n& `( X' B2 A" W3 ADeviation, 离差
: h7 w/ y. ~' [Deviation from average, 离均差! b, l; M5 W. k' b
Diagnostic plot, 诊断图
' {4 l" d. L7 p7 m) A& [Dichotomous variable, 二分变量% o7 R; Z5 v( ~* Q5 T! e
Differential equation, 微分方程
+ k* ~0 L3 ?7 |4 SDirect standardization, 直接标准化法3 h7 J. q7 P# j, G1 ]; @6 {
Discrete variable, 离散型变量5 G+ T1 J8 ^: f* l1 E( D* g
DISCRIMINANT, 判断
) S0 I# A" x# |4 m; nDiscriminant analysis, 判别分析3 {2 ]$ L+ d( X! z
Discriminant coefficient, 判别系数
# z! t% y" q& [, e$ v6 r/ Y) c- {Discriminant function, 判别值! P2 H' W/ S5 [+ F
Dispersion, 散布/分散度' M8 P: ~( z5 x3 ]4 l* j4 d
Disproportional, 不成比例的' F0 Q1 ^. I6 _2 E$ a
Disproportionate sub-class numbers, 不成比例次级组含量
1 Q% z9 ]0 W& e7 d+ |# `! fDistribution free, 分布无关性/免分布/ o/ T3 l: H8 A& p; n6 N
Distribution shape, 分布形状5 i' H$ y, w x6 P L) u
Distribution-free method, 任意分布法0 ~" P o \! `; C9 O( x
Distributive laws, 分配律
' X! r" V A+ h5 pDisturbance, 随机扰动项* A* I. u8 c- y
Dose response curve, 剂量反应曲线
" V; s" R. A* B0 _" F, ]1 j$ Q8 |+ _" pDouble blind method, 双盲法9 }1 C8 ?- s; t0 E9 i
Double blind trial, 双盲试验
: `: U9 X' J mDouble exponential distribution, 双指数分布
" \$ o% R P* r) F* Z+ t- \* i lDouble logarithmic, 双对数$ N8 N2 J* O1 _) k+ M
Downward rank, 降秩
* J* B5 S$ \- ]5 |Dual-space plot, 对偶空间图0 F* i, o# R) x2 A" F' H x
DUD, 无导数方法
' R% Y. z, Q# N8 IDuncan's new multiple range method, 新复极差法/Duncan新法
' m7 t( h) A! r" O( iEffect, 实验效应( N. v* n* [8 |1 b8 E4 L# P4 g
Eigenvalue, 特征值8 W6 t5 f. P# {: B! n+ F
Eigenvector, 特征向量
3 a* U7 w' @( p8 QEllipse, 椭圆
: u4 D2 w% d. V3 [4 C1 AEmpirical distribution, 经验分布$ q+ I9 w1 A4 N* K; {; m
Empirical probability, 经验概率单位
! j# J+ c2 E/ T- R5 sEnumeration data, 计数资料! J; l: S: O8 r* O5 N! z0 C
Equal sun-class number, 相等次级组含量3 Z+ `* ]. W& n( N5 b$ c9 R
Equally likely, 等可能2 `0 v( s% G5 a# A' q. o# U
Equivariance, 同变性
, F! n: J$ E/ |4 tError, 误差/错误
8 V/ Q; O6 ^2 UError of estimate, 估计误差
6 N9 x, U2 E! GError type I, 第一类错误
2 m6 d; |/ D% ]9 [9 p. JError type II, 第二类错误
0 l0 Q. y- n" j0 K2 n3 }Estimand, 被估量
, E7 A1 ]6 W+ v# |8 FEstimated error mean squares, 估计误差均方6 J1 T$ t6 ^6 c
Estimated error sum of squares, 估计误差平方和" H! f$ X5 J. d5 `; H* D
Euclidean distance, 欧式距离
" G* L A# g& w+ n8 x. ?Event, 事件
2 }5 E# k5 {4 AEvent, 事件. H- G$ y0 ~6 c" B
Exceptional data point, 异常数据点
+ ]0 K0 U2 s/ a' K: iExpectation plane, 期望平面
9 q/ c. N6 G/ l8 @Expectation surface, 期望曲面/ R7 H" B& O6 S- o2 e' \
Expected values, 期望值7 V% F/ d6 |2 D
Experiment, 实验
, f* J( W7 j( m0 y2 s- PExperimental sampling, 试验抽样! z# `$ q- e2 j: ]: j( |# |
Experimental unit, 试验单位0 n4 o0 a: G5 F* [0 X
Explanatory variable, 说明变量
8 h9 g( j+ O$ w. b NExploratory data analysis, 探索性数据分析/ {8 m+ d4 {0 D
Explore Summarize, 探索-摘要
1 u/ |9 V" B& E l$ @, S' P$ ]3 Y+ x) @Exponential curve, 指数曲线3 D) A; a; i2 p& U$ ]# Q
Exponential growth, 指数式增长+ Z- {3 S7 B, k7 ?& O- j
EXSMOOTH, 指数平滑方法 8 u- o$ ~% O, T
Extended fit, 扩充拟合
5 c9 Q* K; s6 SExtra parameter, 附加参数
+ p4 S- p% _) s4 _ [; l+ g) jExtrapolation, 外推法2 n a( ]$ {. n
Extreme observation, 末端观测值+ s1 [$ }( e" W1 U
Extremes, 极端值/极值0 e* [0 V# P" x
F distribution, F分布% u, Y. ~) |6 t
F test, F检验
; @/ q: u+ K* D* K7 b% J$ eFactor, 因素/因子
9 | {4 f$ u y$ Z+ C9 lFactor analysis, 因子分析
( J9 B6 u) \% K7 N: f! aFactor Analysis, 因子分析
* g5 U: ~6 t/ V+ E5 @Factor score, 因子得分 $ @& ?0 Y" j3 ^3 k+ y2 I$ X }
Factorial, 阶乘
3 ]. s7 z1 M% u* oFactorial design, 析因试验设计
; ]# r! e) J; _False negative, 假阴性, u4 Q' M( A3 p" L) j* b: |3 s
False negative error, 假阴性错误
) z3 Q2 I& _ G# E7 |3 yFamily of distributions, 分布族+ O' R9 K' T$ T" Q$ w% c
Family of estimators, 估计量族5 x! Y5 M. U& \+ K; r/ U
Fanning, 扇面) n _. L* z& T) ?& J# h5 d
Fatality rate, 病死率
' f/ Z/ g0 y" Z) S3 T# P$ wField investigation, 现场调查
7 S* C- k( [2 i4 fField survey, 现场调查& Z, [+ o; s( |" q* `1 S% s& l
Finite population, 有限总体
% w! |3 Q1 z& s$ JFinite-sample, 有限样本
% W$ D) b( E7 a. _( vFirst derivative, 一阶导数
0 k0 j, c' A" i( ?; g" x. Q- _First principal component, 第一主成分- i8 i& O7 i; x$ s7 I& l
First quartile, 第一四分位数
. d" W3 P e+ b( N* @' jFisher information, 费雪信息量
L; X. L" \; D% _* ], hFitted value, 拟合值
; @8 U/ u& z" W; G4 ~( n' f" `7 z+ yFitting a curve, 曲线拟合! y* D$ k& z" g9 z2 s$ q; m
Fixed base, 定基9 s/ y' j) Z# F1 U6 t
Fluctuation, 随机起伏
* e( i7 a4 o3 R% o* `3 EForecast, 预测
7 T# w8 Q0 \ F7 MFour fold table, 四格表
. m1 W3 s' i9 l# F6 qFourth, 四分点- ^) j# q: C& c" w
Fraction blow, 左侧比率
6 F: @6 s c" Y. s; aFractional error, 相对误差
: C! |( o; g% r7 K2 Q* H: sFrequency, 频率
7 \- o( B' b1 @Frequency polygon, 频数多边图2 w0 [6 D2 Q5 ^; w
Frontier point, 界限点
* u- j1 t" I$ e, |' F( _Function relationship, 泛函关系" n W/ F: s: |) E; W! v9 O' `
Gamma distribution, 伽玛分布
0 @; m. @! t0 r3 c% MGauss increment, 高斯增量
. x% h: g M, GGaussian distribution, 高斯分布/正态分布
1 n1 d+ `$ u0 O8 m( f. EGauss-Newton increment, 高斯-牛顿增量
+ X4 J+ `" k% c- Y4 V8 g5 y: \General census, 全面普查3 p) C; e$ X+ f$ W: o9 D" T
GENLOG (Generalized liner models), 广义线性模型
. W; Y+ s& n d3 S; jGeometric mean, 几何平均数
7 d6 M$ \+ A5 N' \. c& N f! qGini's mean difference, 基尼均差
6 @6 ?; X3 W9 Q) q8 U' `GLM (General liner models), 一般线性模型
v! K0 s0 A" p% ]# B, J5 sGoodness of fit, 拟和优度/配合度: q0 O! I' }/ Y* a
Gradient of determinant, 行列式的梯度
6 F' y7 a, A$ u8 e: B! A9 YGraeco-Latin square, 希腊拉丁方
+ A1 A& c4 b# D2 C% g: v" \3 eGrand mean, 总均值' T; E8 u7 m5 y. ]* g
Gross errors, 重大错误0 d$ A3 }5 R E
Gross-error sensitivity, 大错敏感度 m8 \/ y8 h! l" W" b, Q. }& w
Group averages, 分组平均. U" ?. M4 ?" M" |3 t8 D' U5 I( N
Grouped data, 分组资料" C8 V0 H$ e- B- C. c
Guessed mean, 假定平均数$ B/ U* q8 I/ U7 L C3 i3 [& Y* k
Half-life, 半衰期
5 \# @$ l) r5 ?! PHampel M-estimators, 汉佩尔M估计量
3 U5 w* J0 T2 R. b) L9 b( O2 iHappenstance, 偶然事件 q% Y& y) r5 u9 v9 L7 d5 A
Harmonic mean, 调和均数
1 k* B% }% D EHazard function, 风险均数* Z+ M! x# O! c+ W
Hazard rate, 风险率6 h% e1 |4 `: F' S, l1 F
Heading, 标目 9 L* ~/ o' S: R6 K" H# @
Heavy-tailed distribution, 重尾分布
8 L) h0 t1 ~5 i" A. Q1 _Hessian array, 海森立体阵+ k; k! w2 j$ ~( t( O( ^' \! _
Heterogeneity, 不同质
# o6 B" j& n! _' S; }Heterogeneity of variance, 方差不齐 % Q/ N5 N3 f) K2 }. i
Hierarchical classification, 组内分组% U3 x* O. f; Q' i( u
Hierarchical clustering method, 系统聚类法" Z* K$ z0 }; t+ K+ h8 l; e
High-leverage point, 高杠杆率点
$ \: x* k1 q1 W2 L! w8 q# UHILOGLINEAR, 多维列联表的层次对数线性模型8 ^ ~1 A8 a F# B0 s5 w
Hinge, 折叶点
7 p4 L+ ?: ^, R. a9 CHistogram, 直方图
* z5 _/ f" M7 h6 u" d2 T" t* G$ p" Y! oHistorical cohort study, 历史性队列研究
+ q* K! J# ?) X, } t8 xHoles, 空洞% p- [$ k+ k# g# U# ]
HOMALS, 多重响应分析3 Z$ y$ p: X( Q" M
Homogeneity of variance, 方差齐性/ r% i% x9 p7 E2 p E% u9 Q
Homogeneity test, 齐性检验
3 w4 x+ I8 {/ |4 J. V4 L: W! ~Huber M-estimators, 休伯M估计量. }8 k) `. d& v0 ?) s4 S
Hyperbola, 双曲线7 f8 G/ `, ]' K s% H8 X
Hypothesis testing, 假设检验' ]1 A# Q& \" l2 H' {3 L
Hypothetical universe, 假设总体
4 v3 v% y0 u: o% M _3 l* GImpossible event, 不可能事件) g4 D; Q8 Q$ \& c$ c8 k! E
Independence, 独立性2 ]- ] T, {& t. [; ^& W; m& s* M
Independent variable, 自变量$ d: m% ~; A) v. g
Index, 指标/指数7 e5 b& V8 O2 C" B7 h6 ^$ P) j
Indirect standardization, 间接标准化法; v( D$ k+ i) c6 e2 b+ a
Individual, 个体
" }4 v5 f- s2 x" L9 X& I+ WInference band, 推断带. R( w8 j# L8 C7 X* z. S
Infinite population, 无限总体
; q2 H" `* b" }! yInfinitely great, 无穷大- J7 F' {6 K2 L9 h5 x* M! g
Infinitely small, 无穷小
1 O7 o C' e; V, c, B) XInfluence curve, 影响曲线
5 A1 L! s0 o$ PInformation capacity, 信息容量; ~0 C% ?+ A9 e6 ~
Initial condition, 初始条件" W0 Y, R/ o( \ e X; |8 W
Initial estimate, 初始估计值
% x0 A. Q; f9 l8 i6 LInitial level, 最初水平
* z9 P" T! k5 m- f$ ~5 }2 p7 cInteraction, 交互作用
; L$ ?1 G1 r* r! N5 O$ w9 pInteraction terms, 交互作用项
1 d' g" v# K0 }1 M+ i3 r g, q+ D1 qIntercept, 截距5 ~* c% S$ T/ G' M/ S
Interpolation, 内插法5 o( P$ X0 R3 z6 u7 L/ }7 `8 h
Interquartile range, 四分位距
. `- v1 h+ J) ^0 g8 s8 M, K1 V9 HInterval estimation, 区间估计
+ Y0 D! I. `& p0 K' F, X$ B% l( jIntervals of equal probability, 等概率区间
^, ^' `8 |. c+ jIntrinsic curvature, 固有曲率
( [& {" k( l7 c0 c/ U/ R* V5 HInvariance, 不变性
) j4 n3 q/ J4 F5 G/ c2 Y5 k( t/ HInverse matrix, 逆矩阵
F6 [9 l; d3 P6 {Inverse probability, 逆概率4 @8 `$ I/ c/ g$ j4 H3 w4 D2 M( r
Inverse sine transformation, 反正弦变换
, L |% e! f4 l f; ^Iteration, 迭代
8 \8 ~, `) F+ S9 g, ^# b0 KJacobian determinant, 雅可比行列式4 `; h9 H2 \' V" E3 [: n9 T* N
Joint distribution function, 分布函数7 f: s) Z, `" c/ C4 U+ n
Joint probability, 联合概率$ ?0 u! z9 y! q7 D; b" F
Joint probability distribution, 联合概率分布; n' I& \+ ~# ~9 I- ~/ B) I
K means method, 逐步聚类法
9 D9 ]+ o; \. H- [& gKaplan-Meier, 评估事件的时间长度
- \6 J' D' N u% ]5 @( a8 W; hKaplan-Merier chart, Kaplan-Merier图
0 i1 Z" h) t& z3 X" I1 _Kendall's rank correlation, Kendall等级相关- U) w) J* v5 A) ~7 G/ F
Kinetic, 动力学
o. F, s. H: E% \9 x% ~! jKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验- @, d* |; H6 ]3 p* ]2 J7 u6 h
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
. a+ O0 W! ^5 `5 U% XKurtosis, 峰度) F" k3 {% u* |; X
Lack of fit, 失拟
+ W& C; Q* P. i* [3 Z3 P# TLadder of powers, 幂阶梯
9 @2 b l! @) ^# Z' y. LLag, 滞后: P9 x1 @) O0 R# r3 H/ \
Large sample, 大样本
$ B* d. G8 s7 ^3 i/ {% a% l' `Large sample test, 大样本检验
/ X5 i2 W4 p! ELatin square, 拉丁方
" ]. {3 ~4 L E$ P) YLatin square design, 拉丁方设计! q1 ~3 \3 e: H8 J( ~# Y
Leakage, 泄漏
; k+ d0 @6 u6 PLeast favorable configuration, 最不利构形( L$ Y9 f( A% y" }) F7 a
Least favorable distribution, 最不利分布# \8 Q+ X2 m1 `+ h. P% a; H9 @
Least significant difference, 最小显著差法
+ S1 R& z4 E. g* A `$ h, {Least square method, 最小二乘法+ u) q5 `5 V0 E4 K
Least-absolute-residuals estimates, 最小绝对残差估计
c8 w' I r1 N- z; ILeast-absolute-residuals fit, 最小绝对残差拟合/ I$ I' Z& a9 Q1 `
Least-absolute-residuals line, 最小绝对残差线
, M2 E3 Q: [1 S' y1 N) J2 l* TLegend, 图例 p4 A$ }9 X, _8 m
L-estimator, L估计量
7 c1 [4 G5 y2 s3 U$ w" IL-estimator of location, 位置L估计量8 J: M! u3 Y0 M T7 v% O6 l
L-estimator of scale, 尺度L估计量/ @& @( m, g2 g+ Q, ?2 y: ?
Level, 水平
1 a1 K# u; R2 V$ m4 G J+ D8 j' M: U6 D7 YLife expectance, 预期期望寿命
, {$ z7 }0 X2 y% {1 uLife table, 寿命表1 l: t$ Q7 Y+ X b' F7 ^7 n
Life table method, 生命表法5 P- D% @1 Y6 P
Light-tailed distribution, 轻尾分布8 o- C/ x" l7 p% N7 m$ O
Likelihood function, 似然函数
1 ]3 {8 l7 v7 `/ `6 MLikelihood ratio, 似然比
) l- b* f5 ^5 [9 c7 wline graph, 线图4 E: |7 R' O5 W7 y( o( \" Q
Linear correlation, 直线相关
% B6 \# b/ a& O; c) JLinear equation, 线性方程
6 k; _5 J) \+ g5 O: ]Linear programming, 线性规划
$ n3 v8 a" I6 ^+ uLinear regression, 直线回归0 P+ {5 D0 i/ @3 M" F
Linear Regression, 线性回归
$ Y1 J$ e$ S0 g2 w( gLinear trend, 线性趋势
( s: n( b. f3 b* V7 lLoading, 载荷
* a& e3 X4 P. ]Location and scale equivariance, 位置尺度同变性. B( i: |3 g9 m7 A2 c
Location equivariance, 位置同变性; w: ?+ S( h/ T2 z3 a
Location invariance, 位置不变性
4 I- c6 D' V5 l! vLocation scale family, 位置尺度族
+ T3 Q' m8 v% U. E$ n$ x# \* _2 [Log rank test, 时序检验
6 y7 O1 k4 Q$ P5 T5 E* nLogarithmic curve, 对数曲线
/ d0 H8 K. `7 @. }3 |: f) `3 gLogarithmic normal distribution, 对数正态分布, M5 G' }; M% e; e' Y Q( z
Logarithmic scale, 对数尺度, L9 |" {9 u' V# W3 m% f
Logarithmic transformation, 对数变换) c" z2 m( m8 o# K2 m
Logic check, 逻辑检查
7 L$ F. U& |6 u B6 DLogistic distribution, 逻辑斯特分布
* c7 G; j, w6 L5 ALogit transformation, Logit转换
5 x# z: I" c0 Z, e7 |5 q0 | kLOGLINEAR, 多维列联表通用模型 2 I1 b, `9 c Y$ K+ ]
Lognormal distribution, 对数正态分布; k* x+ l# k( r
Lost function, 损失函数( Q' J G$ L$ a" R* I
Low correlation, 低度相关2 e- Y" B/ a$ n1 x1 b
Lower limit, 下限
' z& I" ]2 R: i- gLowest-attained variance, 最小可达方差
6 F/ V8 b0 ]0 H+ H7 x+ M0 T+ ALSD, 最小显著差法的简称
7 A6 M, a8 K$ i+ MLurking variable, 潜在变量# U- q* x9 L: R; u- H# Q: L
Main effect, 主效应/ g5 ^, x2 ]1 c) a: L2 x% i$ w$ B
Major heading, 主辞标目! f' y- Q! x* P: O+ C3 P+ R5 K
Marginal density function, 边缘密度函数. D7 t; L* k$ Q( [8 x
Marginal probability, 边缘概率
) P! g3 g) y5 `# VMarginal probability distribution, 边缘概率分布
3 y$ V7 [" G0 E1 NMatched data, 配对资料
/ k' e6 P2 o: ]1 u( I0 J5 [+ p" wMatched distribution, 匹配过分布: w6 D. t2 o* @( h
Matching of distribution, 分布的匹配
2 X+ L2 c( u5 j) pMatching of transformation, 变换的匹配
: m# m& [& Q& JMathematical expectation, 数学期望2 X1 _4 Z: Y# ]$ A: h
Mathematical model, 数学模型, P& {4 b2 L3 O( |" D. I# W
Maximum L-estimator, 极大极小L 估计量
4 o8 q& f& {) `4 u( D& i2 @Maximum likelihood method, 最大似然法+ P/ K- c* C# L" E0 I
Mean, 均数# @( c8 K0 v) G
Mean squares between groups, 组间均方
: ]" `: l. C$ X5 @! Q' d R* Y: z$ ~9 nMean squares within group, 组内均方
6 J8 E* l6 S) f K! GMeans (Compare means), 均值-均值比较: P' [: m" t$ c+ f! b$ w
Median, 中位数1 c: E0 r, S8 h }
Median effective dose, 半数效量
9 Q5 k) q5 ^. \+ n8 |3 z5 wMedian lethal dose, 半数致死量
3 i; h x, }( I$ a: Y' ~7 r' tMedian polish, 中位数平滑
3 Z( m9 q. @5 G4 q9 U" pMedian test, 中位数检验6 R" X: h7 W4 c1 d R+ v; {; J
Minimal sufficient statistic, 最小充分统计量. h! H5 z' a Y' V
Minimum distance estimation, 最小距离估计! D I8 c& n0 o. A: w+ G6 E$ t
Minimum effective dose, 最小有效量$ M D# x- m0 F& ~! s I* p! a
Minimum lethal dose, 最小致死量
' k1 I: i" r+ l: f' Q3 Q: i( T3 B8 m) vMinimum variance estimator, 最小方差估计量' _( `* g, k7 C- ~$ s/ b {$ f
MINITAB, 统计软件包8 S" N/ n! b9 }3 P+ n
Minor heading, 宾词标目
. e# n; I7 W' {( A0 f- R& ^Missing data, 缺失值9 ?" Y- b9 Z3 ~' u9 P; ?, n
Model specification, 模型的确定1 h- X0 ^+ a; R( ^ i0 @- K
Modeling Statistics , 模型统计. [$ {, P2 Z# F
Models for outliers, 离群值模型6 T; B2 Z+ r$ O
Modifying the model, 模型的修正* }+ h$ ~. X4 N/ T
Modulus of continuity, 连续性模0 K$ K* r6 Z* K" t5 Z
Morbidity, 发病率 & f5 ~- @$ U) J( G
Most favorable configuration, 最有利构形9 x5 r- |- K% q1 X- w' J& _
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
/ @- m+ X0 S: l: g* ^Multinomial Logistic Regression , 多项逻辑斯蒂回归
7 ?) z& y9 }! u$ gMultiple comparison, 多重比较
; O2 A( g% U1 m+ f. W: N* g& }( cMultiple correlation , 复相关5 I+ E- w( x* s: M7 m5 }( u8 u
Multiple covariance, 多元协方差; s' k9 w. g8 c) G2 s G1 s' L
Multiple linear regression, 多元线性回归# ~; a# ^! O9 `
Multiple response , 多重选项; z- U3 `" K5 }
Multiple solutions, 多解
2 f7 N2 ?: i* OMultiplication theorem, 乘法定理, r. O6 E0 R% ]0 j5 k$ L" Z! g. q
Multiresponse, 多元响应; ]& A' R3 V8 E" `" H
Multi-stage sampling, 多阶段抽样
! ?* G( I* C# tMultivariate T distribution, 多元T分布
) u% H3 m& e. H+ `1 kMutual exclusive, 互不相容$ b* Y9 W, E" g0 g
Mutual independence, 互相独立" h# B2 j# u2 k* W4 f4 q
Natural boundary, 自然边界
" [5 V. Y) a+ ~; n3 g- k" ]4 uNatural dead, 自然死亡2 i5 _" r o L9 u3 E; O+ Y/ D
Natural zero, 自然零, l0 |0 u1 z" o4 Z" q
Negative correlation, 负相关) _+ i$ Y/ f: r5 |
Negative linear correlation, 负线性相关1 g. c- w; G- v3 f5 P# O
Negatively skewed, 负偏
8 ~3 h# H+ U0 n5 f7 g* q A( nNewman-Keuls method, q检验1 B2 h7 y( l1 \+ D4 e5 ?
NK method, q检验
" j+ i; r0 W ^; z: zNo statistical significance, 无统计意义; Y4 C: v. q ]" `# P. b% w
Nominal variable, 名义变量/ `8 F5 R' s) I
Nonconstancy of variability, 变异的非定常性
. G- V- z, h" X" HNonlinear regression, 非线性相关! x0 p0 o0 P& \3 o
Nonparametric statistics, 非参数统计
M( H1 b$ g' L; n! c9 u+ K6 ENonparametric test, 非参数检验- |3 w1 R6 b* O* w( C5 H
Nonparametric tests, 非参数检验/ V) h' N! {& V5 r+ F* L
Normal deviate, 正态离差
. {; x& ?- C% E! X( BNormal distribution, 正态分布6 N, y# x: B# G/ h, o3 P- J6 ^
Normal equation, 正规方程组
: M" T. K6 I0 s1 T/ g1 A2 WNormal ranges, 正常范围" n! J3 i1 [# z; o* N y" i
Normal value, 正常值
/ V9 B6 l( O0 g2 k$ W- PNuisance parameter, 多余参数/讨厌参数
5 B3 J4 N) }3 [Null hypothesis, 无效假设 0 T( k. B) Z3 k5 o4 g+ C7 ^# r
Numerical variable, 数值变量
* j, i& o! a6 n5 KObjective function, 目标函数! S5 [: f; J2 S4 Y9 a
Observation unit, 观察单位# R5 J8 V/ q1 T! n7 d
Observed value, 观察值
% @" h9 C+ X4 V7 Q5 LOne sided test, 单侧检验0 Q" E- i3 j& e5 d
One-way analysis of variance, 单因素方差分析
0 i# @1 X9 T( Q3 T/ ?% BOneway ANOVA , 单因素方差分析2 Y, B. c- @& W
Open sequential trial, 开放型序贯设计
2 R Z; l) Z4 [& D9 y( T5 M) pOptrim, 优切尾
( _$ j5 Y7 s c& m' XOptrim efficiency, 优切尾效率. F: A' O) r) S' A( u: {8 ]
Order statistics, 顺序统计量
. X9 B% j$ o8 g/ y( i" L! @Ordered categories, 有序分类5 X: _. c% [! _3 Q3 Q
Ordinal logistic regression , 序数逻辑斯蒂回归( ^4 {( c2 J+ g7 p3 J
Ordinal variable, 有序变量
# C3 |6 ~% L* J" T; A. x- c2 JOrthogonal basis, 正交基
# m1 O! b9 H$ D# COrthogonal design, 正交试验设计
% S$ H7 C6 r+ s$ \2 }4 pOrthogonality conditions, 正交条件5 {/ d+ A2 F( Y! W/ E1 \# m: T
ORTHOPLAN, 正交设计 + M: ]& P( P0 n' t3 g; p- z
Outlier cutoffs, 离群值截断点% D9 @9 ^' R- f3 B a- B
Outliers, 极端值* f$ V, [% M3 x6 J7 N
OVERALS , 多组变量的非线性正规相关
& E- s# b* i& m: b1 [2 tOvershoot, 迭代过度 W8 x" d" V2 K5 x" W( P
Paired design, 配对设计
! O) y7 h# V1 ^6 [ {0 FPaired sample, 配对样本
% `/ W4 {% ?4 H5 }; ~ V" l+ M5 x NPairwise slopes, 成对斜率
' M% G" \* J- v! [$ ^, G! TParabola, 抛物线+ a9 N8 P: t6 P3 J+ t" [3 V1 X- X
Parallel tests, 平行试验
, O) T' @2 e* eParameter, 参数
# F9 D! t3 H2 {+ \+ t- m8 W* C% E1 Q5 gParametric statistics, 参数统计
X* _$ w& T9 @; t7 n2 t" F2 p. NParametric test, 参数检验6 Q0 B& t6 d2 Z5 f: r
Partial correlation, 偏相关% ]$ D) e8 s' k o1 d. |& d; S# [
Partial regression, 偏回归
' q& c# B. C% b4 T$ k9 P$ rPartial sorting, 偏排序
2 G" f3 e! j& F( QPartials residuals, 偏残差
1 }: y% z- P6 m% R7 G5 b. b- |Pattern, 模式
2 z* y: s( F: X; j, LPearson curves, 皮尔逊曲线8 {& f' N' V. X# r: _8 r
Peeling, 退层: d: W4 y8 \. W1 T7 L
Percent bar graph, 百分条形图
# b/ G+ _6 H# t: \, _5 fPercentage, 百分比
4 G. a& n- [# d& H \Percentile, 百分位数
# f. J2 Y2 A( n* nPercentile curves, 百分位曲线$ M& k+ c5 f( d. G% K
Periodicity, 周期性
; P% o- a- `5 ]: V1 g# e ^# g0 p' jPermutation, 排列
4 P9 @. E4 E$ HP-estimator, P估计量! @0 i% m: f% _6 Y# r
Pie graph, 饼图* v, s/ Q7 `& [5 D0 C6 d
Pitman estimator, 皮特曼估计量8 D* J e, g3 o7 h6 f* N
Pivot, 枢轴量
: T9 G5 Y g& c r6 Y/ s. \4 ~9 JPlanar, 平坦
* R; ~8 D- S( ]4 R2 N9 g9 fPlanar assumption, 平面的假设6 {5 d! y( v* S# y1 s
PLANCARDS, 生成试验的计划卡
" v( P% I6 O1 i5 F6 \1 WPoint estimation, 点估计
" E) p- w% [% L WPoisson distribution, 泊松分布5 p" V5 I O9 g) d) w
Polishing, 平滑
7 H: J* `! O0 i+ `7 OPolled standard deviation, 合并标准差
6 k4 h; G# {6 D, \2 g4 b' F' S4 c2 kPolled variance, 合并方差4 X) z3 \. r$ g6 y+ S# Q& ?9 e
Polygon, 多边图8 ^8 s; T# N1 S% J! Q
Polynomial, 多项式; Q; ]. P0 ^; o* {8 }0 a
Polynomial curve, 多项式曲线
3 B4 W$ u+ g- D" ^! [$ _8 n' G3 fPopulation, 总体
+ l, @- a* x; `( `0 xPopulation attributable risk, 人群归因危险度
* l1 b* h, [$ z' K5 ?Positive correlation, 正相关+ O% s' N" |4 q
Positively skewed, 正偏$ w& h W6 x( N
Posterior distribution, 后验分布* a1 h2 |) D6 D$ t% @
Power of a test, 检验效能) V5 p* T5 k1 b
Precision, 精密度$ y1 `8 W }$ ~8 n" \ m# r
Predicted value, 预测值: B& `* F( }# x) F M: ]
Preliminary analysis, 预备性分析/ o! ?# l, Q' z; h& M8 j) g9 \# A1 N9 w
Principal component analysis, 主成分分析
3 g" P0 ]8 Q o' L# ^Prior distribution, 先验分布
9 t, x0 c$ C [& M- G$ YPrior probability, 先验概率0 H. y- {$ y! A" I9 @% D$ z
Probabilistic model, 概率模型
) I: m, D7 [0 yprobability, 概率
1 [; m6 w* o+ c i$ f* r0 sProbability density, 概率密度+ A1 v- X# G. D6 m* m1 T" S6 r4 u& y4 ]
Product moment, 乘积矩/协方差
5 {% o: |6 s- l! Y" j& `" V# jProfile trace, 截面迹图
( v, v$ Q1 m$ R, T. S2 k/ a" WProportion, 比/构成比/ H8 }% ~( G% C) [
Proportion allocation in stratified random sampling, 按比例分层随机抽样% v0 C" d0 X7 d" q0 r m3 z
Proportionate, 成比例, m: O# \) y; ]9 U+ F4 d
Proportionate sub-class numbers, 成比例次级组含量) U J% o0 [$ `& |0 \8 {0 n
Prospective study, 前瞻性调查 f7 i: m1 {: _' I( D: q! S y. a
Proximities, 亲近性 . ]2 u' c' s# C# A( ]- ?& [
Pseudo F test, 近似F检验
d' y$ Q2 E1 r0 W& q0 z2 n2 I5 uPseudo model, 近似模型8 Q, _5 k& X7 K; z' v
Pseudosigma, 伪标准差
* k' m, O7 d# a- OPurposive sampling, 有目的抽样! q, Z9 C6 j! Z V' U
QR decomposition, QR分解
1 W- q4 l8 n7 C$ ^Quadratic approximation, 二次近似
4 T: U- [! Q6 bQualitative classification, 属性分类
, I- S8 I3 p+ \# a" bQualitative method, 定性方法
1 r9 w) a# d M$ Y+ A2 yQuantile-quantile plot, 分位数-分位数图/Q-Q图; U1 ]! d, k+ S m
Quantitative analysis, 定量分析
& v/ a7 a) {& ], w3 Z. DQuartile, 四分位数
$ B z2 G; @: @4 c) cQuick Cluster, 快速聚类
# j4 O8 [/ q# Z7 ~4 m; NRadix sort, 基数排序
6 S7 q' c% Q2 e" H$ E c/ _7 a* d+ ~8 tRandom allocation, 随机化分组
* r, Y3 g6 t: j# ~' FRandom blocks design, 随机区组设计
) Z$ j) L0 |/ y, yRandom event, 随机事件
) M# `" s8 Q1 F. {8 U% H* vRandomization, 随机化* x4 S1 s; t$ G0 H) n
Range, 极差/全距
@! e* B# R' @3 b' Y7 X- ZRank correlation, 等级相关
8 D8 d) y$ v2 A* gRank sum test, 秩和检验
3 a) d( b1 v( f5 J' h% B* S, a% GRank test, 秩检验
) t) @7 d! _. x7 F8 zRanked data, 等级资料
& W& D/ h+ z. m) u" J$ y$ CRate, 比率- }2 l% c6 R/ d, ?8 k Q
Ratio, 比例
4 S7 z% x$ o0 b3 z7 v/ ]' YRaw data, 原始资料1 F: p6 l( \" ]# S! ?4 ]
Raw residual, 原始残差
) r" D0 A2 g7 T1 G8 ` oRayleigh's test, 雷氏检验4 f6 @0 A, U! L
Rayleigh's Z, 雷氏Z值 2 k% u( f( y# V: k" [' |* Q a! F
Reciprocal, 倒数" \4 n1 G D; p* Q" S0 A7 P! g
Reciprocal transformation, 倒数变换5 a! C% d; i2 O# ?& M% d
Recording, 记录3 `" t$ W( x+ s/ t1 s
Redescending estimators, 回降估计量) l* W$ i M+ ~0 Y
Reducing dimensions, 降维
) W$ [9 ?* O2 a2 [6 h& N- hRe-expression, 重新表达9 h9 u q2 I" N& N) Y
Reference set, 标准组8 Y# R7 L: G, w
Region of acceptance, 接受域( T- c: k5 X4 A" f5 l, T
Regression coefficient, 回归系数2 [9 S0 O8 B5 I! B8 @
Regression sum of square, 回归平方和
% ?; c) H, F( u" {, C) L w h( URejection point, 拒绝点& j5 M' X) c) c$ |: V9 \7 ?
Relative dispersion, 相对离散度, c$ K& P, z, t) D8 p# L( L; d. ]- o
Relative number, 相对数, j, h# o" u y
Reliability, 可靠性
( w! g% X n% wReparametrization, 重新设置参数
5 h- j& h0 P9 N" l- U' r* GReplication, 重复
/ e2 I8 C- C6 l7 h+ j, A' mReport Summaries, 报告摘要, q. W( u8 L- E6 W1 [
Residual sum of square, 剩余平方和; r/ ?4 {" S( a" m
Resistance, 耐抗性
3 l0 G3 @( r0 @9 f- FResistant line, 耐抗线
0 r1 U8 E( D A2 A5 S% v# Q qResistant technique, 耐抗技术: e; B( |' V, y9 O/ S) \) L3 M
R-estimator of location, 位置R估计量
0 a# C3 |, M* M# }6 z1 Q5 VR-estimator of scale, 尺度R估计量
- e& Z. p5 ?* c0 V: lRetrospective study, 回顾性调查
( P K4 ?% E: U# X, W* n* T& I8 WRidge trace, 岭迹" g7 a; ?- f7 e
Ridit analysis, Ridit分析5 U9 j) R& c4 t: b0 i% m
Rotation, 旋转
( ^( F% u5 ?2 L' L0 `$ J. CRounding, 舍入" v* {3 E1 `/ }
Row, 行# J5 O" j& c, U5 M
Row effects, 行效应1 j7 z, T# f+ R% z- Z+ e: x
Row factor, 行因素' ?" K6 W o) h D7 W: i
RXC table, RXC表
' r9 h' U$ X& p: [- L& P& I/ Q3 QSample, 样本0 P+ A j! b B/ U0 [! K
Sample regression coefficient, 样本回归系数
0 Q1 i; X! _8 g+ S) _Sample size, 样本量& m3 S1 C% m- M$ ?, C
Sample standard deviation, 样本标准差* d( ~2 Z- G8 p7 V4 o& o
Sampling error, 抽样误差7 B. f' x8 d/ x8 E0 O
SAS(Statistical analysis system ), SAS统计软件包
- H% D4 j$ w4 B% fScale, 尺度/量表
1 U: n9 Y+ a& E* t# rScatter diagram, 散点图5 [& J* _* ~7 j$ E
Schematic plot, 示意图/简图3 R) F8 K$ ]2 E, O
Score test, 计分检验
7 }* X0 x' {8 X5 N4 Q8 K% @0 PScreening, 筛检4 H$ P4 F, L# r: D9 [* A$ m
SEASON, 季节分析 " x& {6 v( N& c) w
Second derivative, 二阶导数
) |$ t2 V+ Q8 X( x7 V# M8 }Second principal component, 第二主成分
" c# f' P8 o" \8 S5 @SEM (Structural equation modeling), 结构化方程模型 1 K2 y4 y/ m7 Q( H
Semi-logarithmic graph, 半对数图* ]( d' a U, l+ ~/ x2 w; m8 U; ]
Semi-logarithmic paper, 半对数格纸+ G6 Y/ M. v1 x* x0 g
Sensitivity curve, 敏感度曲线
% u1 d/ W& Y1 F" NSequential analysis, 贯序分析
' V4 K/ |( N: Y8 ^! n+ m4 m6 S2 fSequential data set, 顺序数据集1 m# H9 I2 t, ?" _
Sequential design, 贯序设计
" P1 }9 y! j3 y' R& }Sequential method, 贯序法
' f6 l5 X. D! ^Sequential test, 贯序检验法
4 H* d; l: ?( W* Y* x( s3 v% MSerial tests, 系列试验. V$ H" f' Q8 F% {
Short-cut method, 简捷法
' U7 N% K& v" R; N# J: O$ eSigmoid curve, S形曲线) S1 l) }. ^3 k/ Y
Sign function, 正负号函数
# A1 A% x: ~, eSign test, 符号检验
) L3 r, o% x! U; H8 {$ TSigned rank, 符号秩
; |4 B, w; b u0 D* ~Significance test, 显著性检验, S3 Z+ Y8 Z6 R l5 d* F
Significant figure, 有效数字
; y0 V/ I9 g+ o. \Simple cluster sampling, 简单整群抽样& Y. Z* e0 c, Q" r+ M& V$ ^
Simple correlation, 简单相关
' c" x) [4 m/ N) ?Simple random sampling, 简单随机抽样/ `- m6 [$ s. U( O0 ]. `3 j* R
Simple regression, 简单回归) f4 m3 t `7 D. x; |9 ?
simple table, 简单表
6 w1 D K8 n, E" n2 vSine estimator, 正弦估计量
1 V* T2 P! B" y0 xSingle-valued estimate, 单值估计
, `6 g+ @$ p. K9 Q) ~, }Singular matrix, 奇异矩阵* o5 }; U" S7 u' J& R' z4 N
Skewed distribution, 偏斜分布
+ @7 A+ d- I- ?# Q+ Y" DSkewness, 偏度0 G; I2 i( k% k( o
Slash distribution, 斜线分布
3 {- {% C! }( o7 H: g- x, i( B* JSlope, 斜率
- z( _$ {- \& S, vSmirnov test, 斯米尔诺夫检验
; `! q0 ~* f6 u) ~Source of variation, 变异来源 @8 j' j' @! o( p
Spearman rank correlation, 斯皮尔曼等级相关; C. I2 ?% b8 S% |* ]
Specific factor, 特殊因子: b. q0 t2 m1 G4 J# _
Specific factor variance, 特殊因子方差
: e3 A) e' o! S3 d$ G9 lSpectra , 频谱
; h; [3 f( |# L2 s8 fSpherical distribution, 球型正态分布
. S( A0 s8 n" V1 y7 USpread, 展布/ N6 b7 q+ u P4 b. b. G( |6 T
SPSS(Statistical package for the social science), SPSS统计软件包
% [5 S3 C* ]) u( X, F0 v3 oSpurious correlation, 假性相关
; w3 a* I' g5 G0 j0 I2 WSquare root transformation, 平方根变换
6 F+ t- x8 ]1 l3 J# v5 DStabilizing variance, 稳定方差
* C6 Q! w$ z: VStandard deviation, 标准差$ f# r; u% f1 M
Standard error, 标准误
& I/ S; v. Z% ]( _; Q; O* rStandard error of difference, 差别的标准误6 ]8 a. O( D" f5 y
Standard error of estimate, 标准估计误差
; Z) q/ {% J% P+ }& [8 U6 pStandard error of rate, 率的标准误5 z, ?- [( K& j5 W
Standard normal distribution, 标准正态分布2 ^8 m# j$ B. ]6 E0 @8 U
Standardization, 标准化6 Y F1 w' J; s" \7 I( f9 O
Starting value, 起始值
# D2 k" S3 g# r! GStatistic, 统计量7 ~- M# w& ]& f0 F
Statistical control, 统计控制
3 ?3 G3 z/ l, e9 }" H& G! l6 i( F5 AStatistical graph, 统计图
( V$ [5 g6 L7 t3 j( ^4 p. \( ]/ TStatistical inference, 统计推断
- P4 j3 r" O7 v7 gStatistical table, 统计表7 E" U; h( O; g5 b) }% H b
Steepest descent, 最速下降法
- F& h' M1 b6 f! v( b' JStem and leaf display, 茎叶图) `$ [( q% E% ~
Step factor, 步长因子
2 P s7 d8 I7 Z( m2 p7 vStepwise regression, 逐步回归 E( Y/ z( ~* p" x/ O; J6 V o
Storage, 存% f) s: W8 O8 W5 J# X' w
Strata, 层（复数）1 Q4 y: v' A9 B3 ]7 ~! o
Stratified sampling, 分层抽样4 u* j) v1 g: S( ]( b g7 l6 \
Stratified sampling, 分层抽样# w/ I; H0 P8 c' k) }0 L) t# ?9 U4 y
Strength, 强度
: p W' R$ P5 c! qStringency, 严密性( q+ m) G4 i1 R( G1 m2 g% h( }
Structural relationship, 结构关系! W& h6 N" w9 i. I% z- G
Studentized residual, 学生化残差/t化残差# f) Y! C$ h# j0 [+ z. x
Sub-class numbers, 次级组含量, Z, S3 N2 J5 d) {" O
Subdividing, 分割+ v" @2 O4 c1 m- A/ E
Sufficient statistic, 充分统计量
9 H/ J+ P. u/ x7 [" B" RSum of products, 积和
- O) b" X5 ]) m9 b! e; ^+ _, q' `Sum of squares, 离差平方和0 F- O% [7 r7 I i! ^8 S
Sum of squares about regression, 回归平方和3 h) o7 W, S: ]" `$ p% I
Sum of squares between groups, 组间平方和) I+ f' w' n$ o% B( j
Sum of squares of partial regression, 偏回归平方和
# `! c2 `0 a' U4 @Sure event, 必然事件
! a2 Z0 N J, _7 ESurvey, 调查; S! s4 F! y; x2 Z1 h4 i1 x
Survival, 生存分析% V" ^0 L, O; z
Survival rate, 生存率4 u( ?+ P2 Q3 L8 Y" ~$ t
Suspended root gram, 悬吊根图0 N* p6 v6 ~" r2 L
Symmetry, 对称4 [: J6 V# R1 f) h9 G
Systematic error, 系统误差, g$ `4 e9 j$ Y
Systematic sampling, 系统抽样
0 G4 }. ]. b9 s) N$ [" n! D; HTags, 标签# Y+ L- R, _5 G
Tail area, 尾部面积2 s# b1 z' A6 H- n2 x f
Tail length, 尾长6 X. z# ]* M0 ^- @
Tail weight, 尾重
' L) `9 M L- T$ f+ |. T* d4 MTangent line, 切线! b/ s R; h, D8 n3 y2 ~; Q5 a
Target distribution, 目标分布
! F5 q# I" D$ {/ nTaylor series, 泰勒级数! ]& T# f; w. n8 E
Tendency of dispersion, 离散趋势
5 H* S' s( Y, @; [+ |Testing of hypotheses, 假设检验
) |2 q i$ k. F# U6 b, @7 ^Theoretical frequency, 理论频数
f1 G; b, O( z5 v& Z' `8 wTime series, 时间序列/ y4 `' `! g: h% b7 J" N" P
Tolerance interval, 容忍区间
6 B. y6 G$ G% ` {6 M# ETolerance lower limit, 容忍下限
5 c: T& ?3 t% K+ k9 G( C8 q, cTolerance upper limit, 容忍上限7 a8 j- U! k+ a; W/ n p$ D: i
Torsion, 扰率
- z- n, c) \! g# _) L7 ^- N" N% dTotal sum of square, 总平方和
7 T/ {, j) W3 p; v& }Total variation, 总变异
( P: a/ Z8 d% @% d' qTransformation, 转换
+ U- b/ v* b0 g9 ]Treatment, 处理
' A) F+ D. {, rTrend, 趋势
7 T C" e$ u7 ~& `" |3 m8 iTrend of percentage, 百分比趋势! ]5 W1 s" C, ?! b7 ], }# D- ^
Trial, 试验
6 N/ v# T/ E- D5 |Trial and error method, 试错法
) E( E7 ]1 r$ e' E4 a- w; JTuning constant, 细调常数
) J: n* `, H" m* b# TTwo sided test, 双向检验
4 }: A7 M, m+ x( I% d, uTwo-stage least squares, 二阶最小平方% Q4 {4 F( E; _8 ]- t
Two-stage sampling, 二阶段抽样7 `# h+ u8 t* q2 i- p3 F
Two-tailed test, 双侧检验
+ ~8 w# B4 u, w% i2 ] nTwo-way analysis of variance, 双因素方差分析1 n, y0 {& b* I/ q. p
Two-way table, 双向表 L1 ^% G. ^2 C7 }9 V) e; p
Type I error, 一类错误/α错误
( f) ^. n- R# \0 P" OType II error, 二类错误/β错误 P. f) \: {1 D. h
UMVU, 方差一致最小无偏估计简称0 x# O! ~2 F0 R" W
Unbiased estimate, 无偏估计- ~/ }8 {5 \( p j. @$ F6 _
Unconstrained nonlinear regression , 无约束非线性回归
% W7 Q% z m {$ D( OUnequal subclass number, 不等次级组含量7 S* l9 _0 L0 G2 s( `
Ungrouped data, 不分组资料
9 D* S. P; w' G# t% DUniform coordinate, 均匀坐标
" l! |3 K4 S" jUniform distribution, 均匀分布3 ^3 ]0 ~, ^0 w4 t
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 C' H `- e2 |; g; V7 L& O8 lUnit, 单元
4 J- P5 w+ O9 @1 f0 zUnordered categories, 无序分类: G* I) @1 H( i$ I( m1 f8 l" [3 w
Upper limit, 上限, |5 I0 [$ C9 x
Upward rank, 升秩- I, ?: ~ e# N
Vague concept, 模糊概念. P }1 K+ [3 }; U: P$ j: H4 }& X
Validity, 有效性! L( x7 f: A/ z# l8 {& Y- @9 i7 G
VARCOMP (Variance component estimation), 方差元素估计
, ]) w* i# Y6 l: h. M& a- z h: VVariability, 变异性; |% q, k1 P" t) Q
Variable, 变量
( v$ e2 Q, C4 J3 [4 h5 `Variance, 方差6 {/ A* T* w. Z0 F- {
Variation, 变异
) g! a8 I5 q/ d) F! ~Varimax orthogonal rotation, 方差最大正交旋转
: u9 J1 V2 N, _8 H) @9 o% L5 u7 j* a2 AVolume of distribution, 容积
+ I. V$ ]7 v; \5 `W test, W检验% B" L2 v& q& ^
Weibull distribution, 威布尔分布
$ Q: ? Z* E( W" e6 y# [& k4 IWeight, 权数
; Q+ z' A `& Y7 d6 `4 ]2 aWeighted Chi-square test, 加权卡方检验/Cochran检验
% d# |6 p5 f2 f' @! R: bWeighted linear regression method, 加权直线回归
( p/ P8 x3 f9 OWeighted mean, 加权平均数
s8 a$ T) L3 A6 H+ U+ xWeighted mean square, 加权平均方差) X* a3 ?% x& a$ H! q; n# o3 V
Weighted sum of square, 加权平方和
+ t# C K- O Y; mWeighting coefficient, 权重系数
5 s8 R9 J* L+ D- _Weighting method, 加权法 1 Y- ~2 l6 N; |' o: v3 Z* ^; P
W-estimation, W估计量
6 c* B' d0 `/ R& E2 ]/ q# \; P1 ZW-estimation of location, 位置W估计量
( I6 F% J6 b, u. T0 o& xWidth, 宽度8 c8 a: Z' s Z7 ^+ `( N
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
+ K7 E; v% E( P: C) f J* EWild point, 野点/狂点
5 V: l$ l) @0 A) t4 A. b. A; q* sWild value, 野值/狂值
% ~/ T E2 s8 a/ f* i {Winsorized mean, 缩尾均值
& Z6 O p( l- E; S6 s' g# oWithdraw, 失访
- F3 O5 Q/ c$ P' ]% E6 BYouden's index, 尤登指数/ L7 u" s% A( D! @7 r
Z test, Z检验$ ]1 o5 t7 y6 ^& y
Zero correlation, 零相关
5 W4 ~& \" Z3 B, |- n( z! t/ uZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
